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2002 | Buch

Ocean Forecasting

Conceptual Basis and Applications

herausgegeben von: Professor Dr. Nadia Pinardi, Professor Dr. John Woods

Verlag: Springer Berlin Heidelberg

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Über dieses Buch

The Advanced Study Courses in the field of Marine Science and Technology were part of the training programme developed from 1989 until 1999 within MAST, the Marine Science and Technology Programme of the European Union. They were related to the core topics of MAST Programme, marine systems research, extreme marine environments, regional Sea research, coastal systems research and engineering, and marine technology. The main objectives of these study courses were to further advance education in topics at the forefront of scien­ tific and technological development in Europe, and to improve the communication between students and experienced scientists on a European and international level. Over the years the Programme sponsored around 30 Advanced Study Courses. They took place in ten different member states of the European Union and their contribution in the formation of a European scientific community was significant. They also encouraged exchanges and contacts with several countries around the world such as United States, the third Mediterranean countries and others. The Course on Ocean Forecasting was one ofthe most successful with regard to its con­ tent, number of applications for participation and students satisfaction. When considering the need for the Advanced Study Course on Ocean Forecast­ ing, it is important to remember that the Oceans and Seas have always played a central role throughout the history of mankind. This is seen from the times of the ancient civilizations ofEgypt and Greece with the Phoenician traders, to the Viking voyages of exploration and discovery in medieval times.

Inhaltsverzeichnis

Frontmatter
1. Strategic Planning for Operational Oceanography
Abstract
The question that I will try to answer in this paper is “ how can national, regional, and international agencies rationally develop a strategy or linked strategies which will tell them whether it is worth investing in an operational ocean observing and forecasting system, and if the answer is positive, how should this investment be planned, implemented, and managed?” We will consider first the motives for establishing the Global Ocean Observing System (GOOS) and its regional components.
Nicholas C. Flemming
2. Satellite Oceanography for Ocean Forecasting
Abstract
This lecture aims at providing a general introduction to satellite oceanography in the context of ocean forecasting. Satellite oceanography is an essential component in the development of operational oceanography. Major advances in sensor development and scientific analysis have been achieved in the last 20 years. As a result, several techniques are now mature (e.g. altimetry, infra-red imagery) and provide quantitative and unique measurements of the ocean system.
Pierre-Yves Le Traon
3. A Marine Information System for Ocean Predictions
Abstract
The quality and management of the coastal and marine environments are particularly delicate issues in current European social, economical and political agendas. However, genuine environmental concerns relating to the sea are often obfuscated and obscurely formulated because of, among other causes, the absence of a steady supply of reliable information.
Giuseppe M. R. Manzella, MFS-VOS Group
4. A Generalization of a Sigma Coordinate Ocean Model and an Intercomparison of Model Vertical Grids
Abstract
Numerical ocean models increasingly make use of σ — coordinate systems. A paper by Gerdes (1993) shows that these coordinate systems can be more general; he termed the generalized form an “s — coordinate” system. The main advantage of the σ or s — system is that, when cast in a finite difference form, a smooth representation of the bottom topography is obtained; one can also easily incorporate a bottom boundary layer as well as a surface boundary layer in those coordinate systems. This is intuitively appealing and Gerdes has shown that superior numerical results are obtained relative to a z — level system. However, in regions of steep topography and crude resolution — a limiting case would be a seamount represented by a single grid point surrounded by a flat bottom — the so-called sigma coordinate pressure gradient error exists (Haney 1991, Mellor et al. 1994, 1998) and at least locally a z — level coordinate system might be preferred. On the other hand, in a recent study, Bell (1997) has shown that the step structure of z — level models lead to vorticity errors and consequent errors in the barotropic component of the flow which, he reports, cause rather large temperature errors (3 to 4° C) on a 1° x 1° grid of an Atlantic Ocean model after 3 months of integration. And it is difficult to model bottom boundary layers in a z — level model (Winton et al. 1998).
George L. Mellor, Sirpa M. Häkkinen, Tal Ezer, Richard C. Patchen
5. Atmospheric Data Assimilation and Quality Control
Abstract
In this paper we discuss the basic physics of the atmospheric data assimilation problem, in order to understand the important factors to be considered in its mathematical solution. The key mathematical technique, the optimal combination of information, is also approached from its Bayesian basics. Much of this is based on earlier papers (e.g. Lorenc, 1986). The novelty of this paper is its bringing together of these in a simple didactic form, following the agreed notation of Ide et al. (1997), with very simple examples to aid in the physical interpretation of the analysis equations.
Andrew C. Lorenc
6. Sequential Data Assimilation for Nonlinear Dynamics: The Ensemble Kalman Filter
Abstract
Sequential data assimilation methods have proven useful for many applications in meteorology and oceanography. For example are most operational weather prediction systems applying a sequential data assimilation technique where observations are “assimilated” into the model whenever they are available.
Geir Evensen
7. Assimilation of Satellite Altimetry in Ocean Models
Abstract
In this chapter we will look at some of the problems, both conceptual and practical, of assimilating one of the most widely available ocean data sets, that from satellite altimeters. The first sections will deal with conceptual issues. We consider how the ocean and atmospheric assimilation problems differ in some respects. We will look at the 4DVar (Four Dimensional Variational Assimilation) and 3D Sequential assimilation techniques to consider their merits from a physical perspective. Results are then shown from twin experiments of a 3D sequential assimilation approach which tries to account for the ocean physics when assimilating altimeter data. In the final sections we will show preliminary results from a study designed to assimilate TOPEX altimeter data into a global ocean model. Many new problems arise when real satellite data are used, some of which have been solved, and some not. We will summarise by describing the present state of the art and speculate on the likely developments over the next few years.1
Keith Haines
8. Ensembles, Forecasts and Predictability
Abstract
The case of weather forecasts represents a mature example of prediction of a complete environmental system. The achievement of such an objective has required the overcoming of several rather formidable obstacles, some of them technical and organizational, but most of them conceptual and scientific, whose successful treatment has constructed the success story we know now.
Antonio Navarra
9. On North Atlantic Intedecadal Variability: A Stochastic View
Abstract
The North Atlantic climate system is characterized by considerable interdecadal variability. We show examples of interdecadal variability in Figs. 9.1 and 9.2. One of the main modes of the atmosphere over the North Atlantic is the North Atlantic Oscillation (NAO) (e.g. van Loon and Rogers (1978), Hurrell (1995)). The NAO is a dipole in sea level pressure (SLP), with centers of action near Island and the Azores (Fig. 9.Ib), originally described by Walker (1924) and Walker and Bliss (1932). Hurrell (1995) defined an index of the NAO by the difference of the SLPs measured at Lisbon (Portugal) and Stykkisholmur (Iceland). Its time evolution (Fig. 9.1a) exhibits considerable interdecadal variability, with a maximum during the beginning of this century, a minimum during the 1960s, and strongly increasing values thereafter up to present. Moreover, there are observed fairly regular quasidecadal [O(10 years)] variations during the most recent decades. The relatively strong upward trend observed during the last 20 years which contributed strongly to the rise in mean Northern Hemisphere surface temperature (Hurrell (1996)) has been the matter of intense scientific debate, since it is not clear as to whether this trend reflects greenhouse warming or is simply an expression of interdecadal variability.
Mojib Latif, Axel Timmermann, Anselm Grötzner, Christian Eckert, Reinhard Voss
10. Strategy for Regional Seasonal Forecasts
Abstract
The topic is numerical weather prediction, in particular air-sea coupled forecasts over the Mediterranean Sea and the surrounding areas. At this stage, it is not certain whether or not this venture will be successful. The key questions are: (Question 1) Are three month forecasts over the Mediterranean Sea possible ? and (Question 2) Are forecast studies of the ocean state or ecological conditions useful ?
Kikuro Miyakoda
11. Rapid Assessment of the Coastal Ocean Environment
Abstract
The concept of Rapid Environmental Assessment (REA) is to provide environmental nowcasts and forecasts accurate and efficient enough to support operational activity in any arbitrary region of the global coastal ocean, and to respond to operational assessment requests effectively on very short notice. Ocean science and technology today are rapidly evolving and recognized as generally involving interdisciplinary processes and interactions on multiple scales in space and time (Robinson et al., 1999a). To deal with the complex ocean forecasts and simulations required both for research and for operations and management, the concept of an Ocean Observing and Prediction System (OOPS) has emerged for assimilating data from the system’s observational network into the system’s forecasts models to generate requisite field estimates (Mooers, 1999; Robinson and the LOOPS Group, 1999). REA requires a rapidly deployable, generic, portable OOPS.
Allan R. Robinson, Jurgen Sellschopp
12. Forecasting of Sea-level, Currents and Sea Ice in the Baltic Sea
Abstract
The development of operational oceanography is, and should be, driven by the users. To satisfy user requirements scientists and maybe more often consultants are producing the tools or systems for an operational service. Even if the needs expressed by the users seem to be impossible to satisfy, rather modest products can often significantly improve the knowledge on which the users base their decisions.
Lennart Funkquist, Hans Dahlin
13. Predictions in the North Sea
Abstract
This chapter aims to address the following
a)
What do we want to predict in shelf seas and why?
 
b)
What can we predict now?
 
c)
What can’t we predict?
 
d)
Anidentification of the underlying enabling factors and constraints in (b) and (c) and thence ways forward.
 
David Prandle
14. Forecasting Wind-driven Ocean Waves
Abstract
The study of wind-generated surface waves on the ocean is important from a physical, a geophysical and a practical point of view. In these lectures I will concentrate on their dynamics and prediction. Over the last 50 years enormous progress has been made in this field (see, for example: Phillips, 1977; WMO, 1988; and Komen et al., 1994), which has resulted in the availability of advanced measurement tools and advanced numerical models, such as the WAM, WAve Model (WAMDI, 1988).
Gerbrand J. Komen
15. A Multivariate Reduced-order Optimal Interpolation Method and its Application to the Mediterranean Basin-scale Circulation
Abstract
For more than a decade, the Ocean Circulation and Prediction Team at LEGOS, Toulouse, has been developing data assimilation methods and conducting data assimilation experiments in various basins of the World Ocean, and in particular in the Mediterranean. Our aims are to study the feasibility of multivariate control of a model trajectory, and to characterize the predictability of the general circulation, seasonal and interannual variability mesoscale eddies, meanders, sub-basin-scale gyres, and response to wind. This chapter deals with the design and modus operandi of a practical algorithm for data assimilation and application to the Mediterranean.
Pierre De Mey, Mounir Benkiran
16. ENSO Predictions with Coupled Ocean Atmosphere Models
Abstract
The strongest signal on the short range climatic time scale, ranging from a few months to several years, is the El Niño/Southern Oscillation Phenomenon (ENSO). It is characterized by a weakening of the trade winds along the equator and a huge redistribution of heat from the western to the eastern tropical Pacific. The impacts of ENSO are felt worldwide through a disruption of the atmospheric general circulation pattern (Ropelewski and Halpert 1987), which leads, for instance, to severe droughts in Northwest Australia and South East Asia during an El Nino event. The Northeast region of Brazil and Zimbabwe are other regions where rainfall variations are highly correlated with ENSO indices and there are many other examples. Off the Peruvian coast, the marine ecosystem is directly affected by the oceanic variations in upwelling, which has a large impact on the fishery industry. For all these regions, reliable ENSO forecasts would offer decision-makers an opportunity to take account of anticipated climate variations, in order to reduce impacts of ENSO on the economy. Thus, it is a logical consequence that the study of ENSO predictability has become a field of major research.
Martin Fischer
17. Toward Marine Environmental Predictions in the Mediterranean Sea Coastal Areas: A Monitoring Approach
Abstract
Marine environmental predictions involve the observation and modeling of physical, biogeochemical processes and parameters, fused by advanced data assimilation schemes that optimally merge the observational and numerical modeling information in order to produce forecasts. The result of such system should be interfaced with socio-economic models of sustainable development and management of marine resources. Fusing the deterministic dynamical information about the marine ecosystem with the socio-economic and political knowledge of the marine environment has not been tried yet but it is one of the outstanding challenges in integrated coastal management studies. This paper tries to show a scientific strategy to predict the physical and biochemical components toward marine environmental predictions, being aware that some considerations could be changed in view of the integration with socio-economic models and issues. Here we use prediction in total analogy with forecasting and thus as synonymous of deterministic prognosis of dynamical variables from a pre-defined initial state of the system.
Nadia Pinardi, Francis Auclair, Claudia Cesarini, Encho Demirov, Serena Fonda Umani, Michele Giani, Giuseppe Montanari, Paolo Oddo, Marina Tonani, Marco Zavatarelli
18. Primitive Equation Modelling of Plankton Ecosystems
Abstract
We start with a technical problem that hindered progress in biological oceanography throughout the 20th century, and show how it will be circumvented in the 21st century. Because of inadequate sampling, very little of our knowledge of population dynamics in the plankton ecosystem is derived from hypothesis-free analysis of observations. On the contrary, most of our knowledge comes from mathematical simulation. But here comes Catch 22: the same sampling problems make it very difficult to collect data that can effectively test the models used to make those simulations. So their credibility depends mainly on the equations used in the models. Equations used in 20th century models did not have secure scientific foundations of the kind that made modern physics work. They were not based on reproducible laboratory experiments.
John Woods
Backmatter
Metadaten
Titel
Ocean Forecasting
herausgegeben von
Professor Dr. Nadia Pinardi
Professor Dr. John Woods
Copyright-Jahr
2002
Verlag
Springer Berlin Heidelberg
Electronic ISBN
978-3-662-22648-3
Print ISBN
978-3-642-08754-7
DOI
https://doi.org/10.1007/978-3-662-22648-3